



"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCAmelCase							:       Optional[int]          =       logging.get_logger(__name__)

__lowerCAmelCase							:       Union[str, Any]          =       {
    '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json''',
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}



class  _lowerCAmelCase     (					SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase      	=							'''gpt_neox'''





		def __init__(       self				,     _lowercase=5_0_4_3_2				,     _lowercase=6_1_4_4				,     _lowercase=4_4				,     _lowercase=6_4				,     _lowercase=2_4_5_7_6				,     _lowercase="gelu"				,     _lowercase=0.25				,     _lowercase=1_0_0_0_0				,     _lowercase=0.0				,     _lowercase=0.0				,     _lowercase=0.1				,     _lowercase=2_0_4_8				,     _lowercase=0.02				,     _lowercase=1E-5				,     _lowercase=True				,     _lowercase=0				,     _lowercase=2				,     _lowercase=False				,     _lowercase=True				,     _lowercase=None				,     **_lowercase				,     )			->    Union[str, Any]:







								'''simple docstring'''

								super().__init__(bos_token_id=_lowercase				,     eos_token_id=_lowercase				,     **_lowercase )
								snake_case_ :			Any            =      vocab_size
								snake_case_ :			int            =      max_position_embeddings
								snake_case_ :			Tuple            =      hidden_size
								snake_case_ :			Optional[int]            =      num_hidden_layers
								snake_case_ :			int            =      num_attention_heads
								snake_case_ :			Optional[Any]            =      intermediate_size
								snake_case_ :			Dict            =      hidden_act
								snake_case_ :			int            =      rotary_pct
								snake_case_ :			Tuple            =      rotary_emb_base
								snake_case_ :			Union[str, Any]            =      attention_dropout
								snake_case_ :			Optional[int]            =      hidden_dropout
								snake_case_ :			Tuple            =      classifier_dropout
								snake_case_ :			str            =      initializer_range
								snake_case_ :			List[str]            =      layer_norm_eps
								snake_case_ :			Dict            =      use_cache
								snake_case_ :			str            =      tie_word_embeddings
								snake_case_ :			Optional[Any]            =      use_parallel_residual
								snake_case_ :			Any            =      rope_scaling
								self._rope_scaling_validation()

								if self.hidden_size % self.num_attention_heads != 0:
														raise ValueError(
														    """The hidden size is not divisble by the number of attention heads! Make sure to update them!""" )





		def  UpperCAmelCase__				(       self )			->    int:







								'''simple docstring'''

								if self.rope_scaling is None:
														return

								if not isinstance(self.rope_scaling				,     _lowercase ) or len(self.rope_scaling ) != 2:
														raise ValueError(
														    """`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, """
														    f'got {self.rope_scaling}' )
								snake_case_ :			Dict            =      self.rope_scaling.get("""type"""				,     _lowercase )
								snake_case_ :			str            =      self.rope_scaling.get("""factor"""				,     _lowercase )
								if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
														raise ValueError(
														    f'`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}' )
								if rope_scaling_factor is None or not isinstance(_lowercase				,     _lowercase ) or rope_scaling_factor <= 1.0:
														raise ValueError(f'`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}' )






'''simple docstring'''

import os

SCREAMING_SNAKE_CASE__     :						Optional[Any]	=  {'''I''': 1, '''V''': 5, '''X''': 1_0, '''L''': 5_0, '''C''': 1_0_0, '''D''': 5_0_0, '''M''': 1_0_0_0}






def 				a  (     UpperCamelCase_    :    str			)       ->	int:
		snake_case__	     =0

		snake_case__	     =0
		while index < len(UpperCamelCase_			) - 1:
				snake_case__	     =SYMBOLS[numerals[index]]
				snake_case__	     =SYMBOLS[numerals[index + 1]]
				if current_value < next_value:
						total_value -= current_value
				else:
						total_value += current_value
				index += 1
		total_value += SYMBOLS[numerals[index]]

		return total_value






def 				a  (     UpperCamelCase_    :    int			)       ->	str:
		snake_case__	     =''

		snake_case__	     =num // 1000
		numerals += m_count * "M"
		num %= 1000

		snake_case__	     =num // 100
		if c_count == 9:
				numerals += "CM"
				c_count -= 9
		elif c_count == 4:
				numerals += "CD"
				c_count -= 4
		if c_count >= 5:
				numerals += "D"
				c_count -= 5
		numerals += c_count * "C"
		num %= 100

		snake_case__	     =num // 10
		if x_count == 9:
				numerals += "XC"
				x_count -= 9
		elif x_count == 4:
				numerals += "XL"
				x_count -= 4
		if x_count >= 5:
				numerals += "L"
				x_count -= 5
		numerals += x_count * "X"
		num %= 10

		if num == 9:
				numerals += "IX"
				num -= 9
		elif num == 4:
				numerals += "IV"
				num -= 4
		if num >= 5:
				numerals += "V"
				num -= 5
		numerals += num * "I"

		return numerals






def 				a  (     UpperCamelCase_    :    str = "/p089_roman.txt"			)       ->	int:
		snake_case__	     =0

		with open(os.path.dirname(UpperCamelCase_			) + roman_numerals_filename			) as filea:
				snake_case__	     =filea.readlines()

		for line in lines:
				snake_case__	     =line.strip()
				snake_case__	     =parse_roman_numerals(UpperCamelCase_			)
				snake_case__	     =generate_roman_numerals(UpperCamelCase_			)
				savings += len(UpperCamelCase_			) - len(UpperCamelCase_			)

		return savings


if __name__ == "__main__":
			print(f"""{solution() = }""")




